Face recognition and identity verification are now critical components of current security and verification technology. The main objective of this review is to identify the most important deep learning techniques that have contributed to the improvement in the accuracy and reliability of facial recognition systems, as well as highlighting existing problems and potential future research areas. An extensive literature review was conducted with the assistance of leading scientific databases such as IEEE Xplore, ScienceDirect, and SpringerLink and covered studies from the period 2015 to 2024. The studies of interest were related to the application of deep neural networks, i.e., CNN, Siamese, and Transformer-based models, in face recogni

The emergence of such widespread pharmaceuticals as a pollutant has become one of the world's critical environmental problems that may lead to both the public's health and biodiversity deterioration. This article provides an exhaustive account of the current understanding of the environmental persistence of pharmaceutical contaminants following in-depth analysis of the additive effects of existing natural biodegradation pathways on the human health impact of these drugs. Paying special attention to biodegradation decomposing agents such as bacteria, fungi, and algae the paper estimates their ability to convert drug ingredients to compound that is eventually less toxic. Although these biologic systems contain an enormous potential fo

With the development of communication technologies, the use of wireless systems in biomedical implanted devices has become very useful. Bio-implantable devices are electronic devices which are used for treatment and monitoring brain implants, pacemakers, cochlear implants, retinal implants and so on. The inductive coupling link is used to transmit power and data between the primary and secondary sides of the biomedical implanted system, in which efficient power amplifier is very much needed to ensure the best data transmission rates and low power losses. However, the efficiency of the implanted devices depends on the circuit design, controller, load variation, changes of radio frequency coil’s mutual displacement and coupling coef

Due to the remarkable progress in photovoltaic technology, enhancing efficiency and minimized the costs have emerged as global challenges for the solar industry. A crucial aspect of this advancement involves the creation of solar cell antireflection coating, which play a significant role in minimizing sunlight reflection on the cell surface. In this study, we report on the optimization of the characteristics of CeO2 films prepared by pulsed laser deposition through the variation of laser energy density. The deposited CeO2 nanostructure films have been used as an effective antireflection coating (ARC) and light-trapping morphology to improve the efficiency of silicon crystalline solar cell. The film’s thickness increases as laser fluence i

   This research seeks to shed light on what you add intangible assets of benefit to the company and this antagonize pause for consideration because it makes the company in a good competitive position stimulates the rest of the companies to acquire those assets.

   That many companies have achieved competitive advantages in the market do not even achieved monopolies increased the value and reaped extraordinary profits as a result of those assets which requires the need to be measured to determine the extent to which contribution in the emergence of the value added to the value of the company on the one hand and to make the presentatio

Background: Medication reconciliation can include medication reviewing and providing counseling and a list of all the medications during every transition of care. Objectives: to explore in-depth the perspectives of Iraqi physicians and pharmacists regarding the necessity of medication reconciliation at hospital discharge and identify the possible benefits and challenges that could face its implementation. Subjects and Methods: A qualitative study included semi-structured interviews with pharmacists and physicians working at a public teaching hospital in Iraq. The interviews were conducted face-to-face from February to March 2023. Thematic analysis was used to analyze the qualitative data generated from the interviews. Results: In th

Thyroid disease is a common disease affecting millions worldwide. Early diagnosis and treatment of thyroid disease can help prevent more serious complications and improve long-term health outcomes. However, thyroid disease diagnosis can be challenging due to its variable symptoms and limited diagnostic tests. By processing enormous amounts of data and seeing trends that may not be immediately evident to human doctors, Machine Learning (ML) algorithms may be capable of increasing the accuracy with which thyroid disease is diagnosed. This study seeks to discover the most recent ML-based and data-driven developments and strategies for diagnosing thyroid disease while considering the challenges associated with imbalanced data in thyroid dise